Cut Your Data Costs With A Unified Data Solution

Data may be costing you more than you know. Server costs, time costs of data management and migration, and the costs of hiring data consultants and using different data tools–it all adds up. While cloud storage is technically infinitely scalable, that scaling comes with exponential cost increases, and the preponderance of tools designed to help make use of data stored in the cloud may also be a drain.  With storage, the multitude of tools, the resources required to gather, manage and secure data, and the price of training and retaining talent, the cost of data is increasing exponentially.

Excess costs can be trimmed in multiple ways, but the easiest, most effective and future-proof way to lower the overall total data cost is by implementing a unified data operations solution. This unique approach to data management not only addresses increasing costs but also eliminates redundant costs at their source by providing all of the functions contained in multiple tools, eliminating inefficiencies and improving accessibility and collaboration across teams.

Consolidate Tools

Data drives innovation, insights, and every other aspect of the modern enterprise, and having tools to ingest, replicate and integrate data is essential. However, maintaining too many tools can cause issues with processes and integration and can create redundant or contrary data storage locations, and many data ecosystems are also becoming highly fragmented due to the multitude of data systems and tools that have been built, adopted, and phased out in the past two decades.

This constant shift is important for staying up-to-date with new innovations in the field, but transitions between tools and systems can cause holes in data flows and/or cracks in pipelines that cause slowdowns or lost data. To provide the quickest, most secure access to the most relevant data in ecosystems that incorporate multiple tools for specific processes, perfectly integrating and training all users in every current data tool is necessary.

A more feasible solution is to consolidate several tools into one, which lowers the cost and resources required to run, integrate, and learn involved tools. This is where a unified data solution comes in—by increasing data flow and eliminating redundant tasks and processes, a unified data solution allows data to be processed faster, more securely, and without any potential integration issues. It also lowers the time and resources required for training and can reduce data management and operations overhead costs.

Requiring teams to learn and operate only one platform is a much smaller cost. Since a unified data solution can ETL from mainframes, retrieve data from SaaS services such as CRM and ad platforms, and provide streaming data flows for business operations, including supply chain and POS data, while also enabling the API-based workflows provided by a traditional iPaas tool, such a solution reduces expenses from your data framework and improves profitability by consolidating your tech stack and encouraging simplicity.

One leading retailer replaced four different technology solutions with Nexla, consolidating their tool usage. By automating the data pipeline process, the retail chain was able to build 500 pipelines within 90 days, freeing up over half of the resources formerly spent on preparing data for analytics.

Making Data Accessible

One of the biggest bottlenecks in data solutions and data processing is associated with the data engineering team due to the sheer amount of data and time required to maintain systems and keep up with requests. By democratizing data and making it available to everyone, the load on these teams can be lightened or lifted entirely. Through automation and self-serve ability creation for teams across business units, the people who need and use data can request it themselves without having to wait in a queue or add work for the data engineering team.

This is why a no/low-code solution is a primary cost-saver in a unified data solution. Less technical (and often less expensive) employees can have the same access to the same data as specialists, consultants, and engineers, freeing up the latter roles to create, innovate, and add value.

A no/low-code unified data solution also lets you scale data pipelines without scaling engineering costs. Since templates, connectors, and custom data transforms can be created in Nexla by engineers and then shared across an organization, everyone can have the same access without addressing individual requests. A unified data solution lets you maintain data security and integrity while providing access to everyone, saving costs of hiring new specialists and scaling pipelines, and minimizing training and deployment costs for each team.

Poshmark implemented Nexla’s unified solution, including a self-service platform, that allows data users to easily access ready-to-use data from internal and third-party sources without spending additional engineering resources, increasing their analytics insights delivery efficiency ten times over.

Minimizing Resources

As with consolidating tools, upon automating data engineering, the required amount of resources becomes much lower. Data teams’ time can be maximized by removing the need to constantly create new data pipelines so that more time can be spent on innovation. Resources can be used for essential value-adding activities instead of pipeline maintenance or creation; instead of hiring a bigger team, get more value out of the team that already knows the work.

By lowering the technical knowledge threshold and onboarding requirements, a no/low-code interface increases collaboration and removes the time and financial cost of training team members. Increasing access to data lets people create self-serve pipelines and get the data they need when they need it and in the format that they use without having to rely on a data team.

Removing data storage and process redundancies also decreases the amount of storage required, and when costs are assessed by usage, this saves costs every month.

Instacart applied Nexla as their unified data solution to maximize resource use and reaped significant benefits. Learn how they sped up time-to-market while reducing their data engineering overhead by five times the previous cost.

Automating Data Products

Data products are the foundation of a fast, automated unified data solution. With automated data product creation and delivery across teams and business units, data can be used anywhere by anyone without any extra steps or costs. A no/low-code interface allows even non-technical users to request and receive the data that they need without going through a data engineering team or requiring extra training.

Data products also increase data quality and governance and facilitate data use monitoring and transparency to allow auditing and consistent security application across an entire enterprise without requiring a dedicated team.

An accurate and consistent data solution increases productivity by lowering data time to analysis and collection times. By further reducing data integration costs through the use of autogenerated connectors, metadata, and automated data products, a unified data solution both eliminates redundant costs and reduces necessary ones.

Nexla’s unified self-service platform allows data users at Poshmark to easily access ready-to-use data from internal and third-party sources without spending additional engineering resources.

One of the top 3 banks in the US saved nearly $8M in data engineering costs by enabling data scientists to obtain ready-to-use data without waiting for data engineering. By automating the most common data engineering workflows with data products, they increased access to data and freed up resources and cut costs while speeding up data processes.

Conclusion

Cost optimization is not a simple, one-time event; it is an ongoing process that requires upkeep and constant decision-making on expenditures and consolidations. While running several small tools may be more cost-effective in the short term, the performance of each tool may not be optimal, and the hidden costs of integrating and training and the resources that support them will also add up.

If rising data costs are on your mind, Nexla can help. Get a demo or book your free unified data solution strategy session today,and learn how much you could be saving on data operations and overhead. For more on data and data solutions, check out the other articles on Nexla’s blog.